Unmanned aerial vehicle (“UAV”) technology has proven to be a valuable tool for mission profiles involving intelligence, surveillance, reconnaissance, and payload delivery. In contexts such as low-altitude urban reconnaissance, a UAV, such as a micro-air vehicle (“MAV”), may encounter both large and small obstacles that may be fixed or moving and whose position is not known in advance. Moreover, because UAVs and MAVs tend to fly in constrained, cluttered environments, they are prone to crashing or colliding with objects. Furthermore, UAVs and MAVs are generally less expensive than traditional aerial vehicles and, as such, are more prevalent and often utilized by less-skilled pilots who may, in turn, cause a collision. Existing technology for preventing UAVs and MAVs from running into objects and other obstacles, such as a Global Positioning System (“GPS”), is generally inadequate, as many objects cannot be recognized via a GPS device and, depending on the terrain, GPS accuracy performance varies widely across environments.
Accordingly, there remains a need for improved autonomous vehicle navigation systems and obstacle-avoidance systems that can respond to varied and unknown obstacles in cluttered navigational environments. Furthermore, there is also a need for an autonomous vehicle navigation or obstacle-avoidance system for augmenting and/or overriding navigation commands communicated to a vehicle.